Dieses Stellenangebot ist nicht mehr verfügbar
Applied AI and Machine Learning Scientist - Senior Associate
JPMorgan Chase & Co.
- London, England, United Kingdom
- London, England, United Kingdom
Über
As a Machine Learning Scientist, you will apply sophisticated machine learning methods to a wide variety of complex tasks including data mining and exploratory data analysis and visualization, text understanding and embedding, anomaly detection in time series and log data, large language models (LLMs) and generative AI for technology use‑cases, reinforcement learning and recommendation systems. You must excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production. You must also have a passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. You must have solid expertise in Deep Learning with hands‑on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.
Job Responsibilities
Research and explore new machine learning methods through independent study, attending industry‑leading conferences and experimentation
Develop state‑of‑the‑art machine learning models to solve real‑world problems and apply them to complex business‑critical problems in Cybersecurity, Software and Technology Infrastructure
Collaborate with multiple partner teams in Cybersecurity, Software and Technology Infrastructure to deploy solutions into production
Drive firmwide initiatives by developing large‑scale frameworks to accelerate the application of machine learning models across different areas of the business
Contribute to reusable code and components that are shared internally and also externally
Required qualifications, capabilities and skills
Masters in a related discipline (e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science) with 2 years experience or PhD with 1 year of industry or research experience in the field.
Hands‑on experience and solid understanding of machine learning and deep learning methods
Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit‑Learn, Pandas)
Extensive experience with large language models (LLMs) and accompanying tools & techniques in the LLM ecosystem (e.g. LangChain, LangGraph, Vector databases, opensource Models, RAG, Agentic Systems & Workflows, LLM fine‑tuning)
Scientific thinking and the ability to invent
Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
Experience with big data and scalable model training
Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
Curious, hardworking and detail‑oriented, and motivated by complex analytical problems
Ability to work both independently and in highly collaborative team environments
Preferred qualifications, capabilities and skills > Strong background in Mathematics and Statistics
In‑depth knowledge and proficiency in agentic frameworks like LangChain and LangGraph and related platforms like LangSmith.
Familiarity with the financial services and related technologies and industries, including familiarity in networking and infrastructure platforms.
Experience with A/B experimentation and data/metric‑driven product development
Experience with cloud‑native deployment in a large scale distributed environment
Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
Ability to develop and debug production‑quality code
Familiarity with continuous integration models and unit test development
#J-18808-Ljbffr
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot wurde von einem unserer Partner veröffentlicht. Sie können das Originalangebot einsehen hier.